Printing and dyeing setting machine energy consumption classification prediction method based on gradient promotion decision tree

Abstract

The invention discloses a printing and dyeing setting machine energy consumption classification prediction method based on a gradient promotion decision tree. The method comprises the following steps:step 1, collecting data tables such as printing and dyeing orders, setting machine process parameters and energy consumption; step 2, carrying out arrangement and data preprocessing on each data table to obtain a preprocessed feature data set; step 3, constructing a setting machine comprehensive energy consumption model, using the setting machine comprehensive energy consumption model for generating predicted values of setting machine energy consumption categories, selecting the preprocessed feature data set in combination with the energy consumption categories, and obtaining a training feature data set; step 4, training the feature data set by using a gradient boosting decision tree classification prediction model to obtain a printing and dyeing setting machine energy consumption category prediction model; and step 5, generating characteristic data of the printing and dyeing order to be predicted, and carrying out prediction by using the prediction model to obtain the energy consumption category of a setting machine. The energy consumption category of a printing and dyeing setting machine is predicted by using a gradient lifting decision tree algorithm, so that the accuracy is relatively high.

Description

technical field [0001] The invention relates to a method for classifying and predicting the energy consumption of a printing and dyeing setting machine based on a gradient lifting decision tree. [0002] technical background [0003] The heat setting process is located in the post-processing section of the printing and dyeing process, and mainly completes the tentering and setting treatment of the fabric. The energy consumption of the setting process is huge, accounting for about one-half of the total energy consumption of printing and dyeing enterprises, mainly composed of gas energy consumption heated by heat transfer oil and electric energy consumed by heat conduction fans. [0004] At present, the printing and dyeing industry generally adopts measures such as optimizing process flow, workshop scheduling, and updating equipment to achieve a certain degree of energy saving and emission reduction, but the effect is relatively limited. With the development of big data and In...

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Problems solved by technology

[0004] At present, the printing and dyeing industry generally adopts measures such as optimizing process flow, workshop scheduling, and updating equipment to achieve a certain degree of energy saving and emission reduction, but the effect is relatively limited

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